Learning and recognition of tactile temporal sequences by mice and humans

Cross-modal implicit learning of random time patterns

Perception is sensitive to statistical regularities in the environment, including temporal characteristics of sensory inputs. Interestingly, implicit learning of temporal patterns in one modality can also improve their processing in another modality. However, it is unclear how cross-modal learning transfer affects neural responses to sensory stimuli. Here, we recorded neural activity of human volunteers using electroencephalography (EEG), while participants were exposed to brief sequences of randomly timed auditory or visual pulses. Some trials consisted of a repetition of the temporal pattern within the sequence, and subjects were tasked with detecting these trials. Unknown to the participants, some trials reappeared throughout the experiment across both modalities (Transfer) or only within a modality (Control), enabling implicit learning in one modality and its transfer. Using a novel method of analysis of single-trial EEG responses, we showed that learning temporal structures within and across modalities is reflected in neural learning curves. These putative neural correlates of learning transfer were similar both when temporal information learned in audition was transferred to visual stimuli and vice versa. The modality-specific mechanisms for learning of temporal information and general mechanisms which mediate learning transfer across modalities had distinct physiological signatures: temporal learning within modalities relied on modality-specific brain regions while learning transfer affected beta-band activity in frontal regions.

Optogenetic manipulation of inhibitory interneurons can be used to validate a model of spatiotemporal sequence learning

The brain uses temporal information to link discrete events into memory structures supporting recognition, prediction, and a wide variety of complex behaviors. It is still an open question how experience-dependent synaptic plasticity creates memories including temporal and ordinal information. Various models have been proposed to explain how this could work, but these are often difficult to validate in a living brain. A recent model developed to explain sequence learning in the visual cortex encodes intervals in recurrent excitatory synapses and uses a learned offset between excitation and inhibition to generate precisely timed "messenger" cells that signal the end of an instance of time. This mechanism suggests that the recall of stored temporal intervals should be particularly sensitive to the activity of inhibitory interneurons that can be easily targeted in vivo with standard optogenetic tools. In this work we examined how simulated optogenetic manipulations of inhibitory cells modifies temporal learning and recall based on these mechanisms. We show that disinhibition and excess inhibition during learning or testing cause characteristic errors in recalled timing that could be used to validate the model in vivo using either physiological or behavioral measurements.

Analogous cognitive strategies for tactile learning in the rodent and human brain

Evolution has molded individual species' sensory capacities and abilities. In rodents, who mostly inhabit dark tunnels and burrows, the whisker-based somatosensory system has developed as the dominant sensory modality, essential for environmental exploration and spatial navigation. In contrast, humans rely more on visual and auditory inputs when collecting information from their surrounding sensory space in everyday life. As a result of such species-specific differences in sensory dominance, cognitive relevance and capacities, the evidence for analogous sensory-cognitive mechanisms across species remains sparse. However, recent research in rodents and humans yielded surprisingly comparable processing rules for detecting tactile stimuli, integrating touch information into percepts, and goal-directed rule learning. Here, we review how the brain, across species, harnesses such processing rules to establish decision-making during tactile learning, following canonical circuits from the thalamus and the primary somatosensory cortex up to the frontal cortex. We discuss concordances between empirical and computational evidence from micro- and mesoscopic circuit studies in rodents to findings from macroscopic imaging in humans. Furthermore, we discuss the relevance and challenges for future cross-species research in addressing mutual context-dependent evaluation processes underpinning perceptual learning.

Non-telecentric two-photon microscopy for 3D random access mesoscale imaging

Diffraction-limited two-photon microscopy permits minimally invasive optical monitoring of neuronal activity. However, most conventional two-photon microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing a non-telecentric optical design, we present a low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view. Moreover, rapid laser-focus control via an electrically tunable lens allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in zebrafish, mice and fruit flies.

Repetition detection and rapid auditory learning for stochastic tone clouds

Stochastic sounds are useful to probe auditory memory, as they require listeners to learn unpredictable and novel patterns under controlled experimental conditions. Previous studies using white noise or random click trains have demonstrated rapid auditory learning. Here, we explored perceptual learning with a more parametrically variable stimulus. These "tone clouds" were defined as broadband combinations of tone pips at randomized frequencies and onset times. Varying the number of tones covered a perceptual range from individually audible pips to noise-like stimuli. Results showed that listeners could detect and learn repeating patterns in tone clouds. Task difficulty varied depending on the density of tone pips, with sparse tone clouds the easiest. Rapid learning of individual tone clouds was observed for all densities, with a roughly constant benefit of learning irrespective of baseline performance. Variations in task difficulty were correlated to amplitude modulations in an auditory model. Tone clouds thus provide a tool to probe auditory learning in a variety of task-difficulty settings, which could be useful for clinical or neurophysiological studies. They also show that rapid auditory learning operates over a wide range of spectrotemporal complexity, essentially from melodies to noise.

Sequence Learning Induces Selectivity to Multiple Task Parameters in Mouse Somatosensory Cortex

Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence discrimination, we developed a task in which mice distinguished between tactile "word" sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a "detection of change" problem, but enhanced their performance when responding later. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory "barrel" cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal's action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal's learned action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf, sequence learning results in neurons whose activity reflects the learned association between target sequence and licking rather than a refined representation of sensory features.

Learning boosts the decoding of sound sequences in rat auditory cortex

Continuous acoustic streams, such as speech signals, can be chunked into segments containing reoccurring patterns (e.g., words). Noninvasive recordings of neural activity in humans suggest that chunking is underpinned by low-frequency cortical entrainment to the segment presentation rate, and modulated by prior segment experience (e.g., words belonging to a familiar language). Interestingly, previous studies suggest that also primates and rodents may be able to chunk acoustic streams. Here, we test whether neural activity in the rat auditory cortex is modulated by previous segment experience. We recorded subdural responses using electrocorticography (ECoG) from the auditory cortex of 11 anesthetized rats. Prior to recording, four rats were trained to detect familiar triplets of acoustic stimuli (artificial syllables), three were passively exposed to the triplets, while another four rats had no training experience. While low-frequency neural activity peaks were observed at the syllable level, no triplet-rate peaks were observed. Notably, in trained rats (but not in passively exposed and naïve rats), familiar triplets could be decoded more accurately than unfamiliar triplets based on neural activity in the auditory cortex. These results suggest that rats process acoustic sequences, and that their cortical activity is modulated by the training experience even under subsequent anesthesia.

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Rats could behaviourally differentiate acoustic stimulus triplets after training.

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Learning relatively increased auditory cortical entrainment to triplets.

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Learning improved decoding of familiar stimuli based on auditory cortical activity.

Low-cost, microcontroller-based, two-channel piezoelectric bender device for somatosensory experiments

Understanding the joint encoding of multiple tactile stimulus features (e.g., spatial position, amplitude, and frequency of vibration) is a major goal of somatosensory neuroscience, and the development of experimental set-ups to probe joint encoding is important. We describe in detail a microcontroller-based, piezoelectric bender device for tactile experiments. The device comprises an Arduino Due microcontroller board with a 32-bit ARM Cortex-M3 RISC processor, and two 12-bit digital-to-analog converters, enabling precise, independent stimulation of adjacent epithelial points. Using laser doppler vibrometry, we developed a model of the benders' structural mechanics, which we implemented on the device. We used the device to delivered precise, reliable somatosensory stimulation in an experimental setting, recording electrophysiological responses in the peripheral nervous system of the Gisborne cockroach (Drymaplaneta semivitta) to sinusoidal vibration of tibial spines. We plotted tuning curves and derived bandwidths of multi-unit populations. We also stimulated rat facial vibrissae ex vivo. This microcontroller-based, low-cost, open-source system leverages a large developer community associated with Arduino, and may help speed advances in systems neuroscience.

Long-term implicit memory for sequential auditory patterns in humans

Memory, on multiple timescales, is critical to our ability to discover the structure of our surroundings, and efficiently interact with the environment. We combined behavioural manipulation and modelling to investigate the dynamics of memory formation for rarely reoccurring acoustic patterns. In a series of experiments, participants detected the emergence of regularly repeating patterns within rapid tone-pip sequences. Unbeknownst to them, a few patterns reoccurred every ~3 min. All sequences consisted of the same 20 frequencies and were distinguishable only by the order of tone-pips. Despite this, reoccurring patterns were associated with a rapidly growing detection-time advantage over novel patterns. This effect was implicit, robust to interference, and persisted for 7 weeks. The results implicate an interplay between short (a few seconds) and long-term (over many minutes) integration in memory formation and demonstrate the remarkable sensitivity of the human auditory system to sporadically reoccurring structure within the acoustic environment.

Making sense of sensory evidence in the rat whisker system

In natural environments, choices frequently must be made on the basis of complex and ambiguous streams of sensory input. There are advantages inherent to rapid decision making. Choices are better grounded, however, if information is acquired and accumulated over time. In primate visual motion perception, sensory evidence is accumulated up to a limit, at which point the brain commits to a choice. Recalling the models evoked for primate visual perception, recent studies in the rat vibrissal sensorimotor system, using a number of behavioral paradigms, show that perceptual decision making is characterized by the integration of sensory evidence over time. In this integrative process, vibrissal primary somatosensory cortex (vS1 and vS2) act not as the integrator, but as the distributor of sensory information to downstream regions.

Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues during Active Tactile Decision Making

Perceptual decision making is an active process where animals move their sense organs to extract task-relevant information. To investigate how the brain translates sensory input into decisions during active sensation, we developed a mouse active touch task where the mechanosensory input can be precisely measured and that challenges animals to use multiple mechanosensory cues. Male mice were trained to localize a pole using a single whisker and to report their decision by selecting one of three choices. Using high-speed imaging and machine vision, we estimated whisker-object mechanical forces at millisecond resolution. Mice solved the task by a sensory-motor strategy where both the strength and direction of whisker bending were informative cues to pole location. We found competing influences of immediate sensory input and choice memory on mouse choice. On correct trials, choice could be predicted from the direction and strength of whisker bending, but not from previous choice. In contrast, on error trials, choice could be predicted from previous choice but not from whisker bending. This study shows that animal choices during active tactile decision making can be predicted from mechanosensory and choice-memory signals, and provides a new task well suited for the future study of the neural basis of active perceptual decisions.SIGNIFICANCE STATEMENT Due to the difficulty of measuring the sensory input to moving sense organs, active perceptual decision making remains poorly understood. The whisker system provides a way forward since it is now possible to measure the mechanical forces due to whisker-object contact during behavior. Here we train mice in a novel behavioral task that challenges them to use rich mechanosensory cues but can be performed using one whisker and enables task-relevant mechanical forces to be precisely estimated. This approach enables rigorous study of how sensory cues translate into action during active, perceptual decision making. Our findings provide new insight into active touch and how sensory/internal signals interact to determine behavioral choices.

Memory for Random Time Patterns in Audition, Touch, and Vision

Perception deals with temporal sequences of events, like series of phonemes for audition, dynamic changes in pressure for touch textures, or moving objects for vision. Memory processes are thus needed to make sense of the temporal patterning of sensory information. Recently, we have shown that auditory temporal patterns could be learned rapidly and incidentally with repeated exposure [Kang et al., 2017]. Here, we tested whether rapid incidental learning of temporal patterns was specific to audition, or if it was a more general property of sensory systems. We used a same behavioral task in three modalities: audition, touch, and vision, for stimuli having identical temporal statistics. Participants were presented with sequences of acoustic pulses for audition, motion pulses to the fingertips for touch, or light pulses for vision. Pulses were randomly and irregularly spaced, with all inter-pulse intervals in the sub-second range and all constrained to be longer than the temporal acuity in any modality. This led to pulse sequences with an average inter-pulse interval of 166 ms, a minimum inter-pulse interval of 60 ms, and a total duration of 1.2 s. Results showed that, if a random temporal pattern re-occurred at random times during an experimental block, it was rapidly learned, whatever the sensory modality. Moreover, patterns first learned in the auditory modality displayed transfer of learning to either touch or vision. This suggests that sensory systems may be exquisitely tuned to incidentally learn re-occurring temporal patterns, with possible cross-talk between the senses.

Organization of sensory feature selectivity in the whisker system

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Neurons in the whisker system are selective to spatial and dynamical properties – features – of sensory stimuli.

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At each stage of the pathway, different neurons encode distinct features, generating a rich population representation.

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Whisker touch is robustly represented; neurons respond to touch-driven fast fluctuations in forces at the whisker base.

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Cortical neurons have more complex and context-dependent selectivity than subcortical, e.g., to collective whisker motion.

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Understanding how these signals are integrated to construct whisker-mediated percepts requires further research.

Our sensory receptors are faced with an onslaught of different environmental inputs. Each sensory event or encounter with an object involves a distinct combination of physical energy sources impinging upon receptors. In the rodent whisker system, each primary afferent neuron located in the trigeminal ganglion innervates and responds to a single whisker and encodes a distinct set of physical stimulus properties – features – corresponding to changes in whisker angle and shape and the consequent forces acting on the whisker follicle. Here we review the nature of the features encoded by successive stages of processing along the whisker pathway. At each stage different neurons respond to distinct features, such that the population as a whole represents diverse properties. Different neuronal types also have distinct feature selectivity. Thus, neurons at the same stage of processing and responding to the same whisker nevertheless play different roles in representing objects contacted by the whisker. This diversity, combined with the precise timing and high reliability of responses, enables populations at each stage to represent a wide range of stimuli. Cortical neurons respond to more complex stimulus properties – such as correlated motion across whiskers – than those at early subcortical stages. Temporal integration along the pathway is comparatively weak: neurons up to barrel cortex (BC) are sensitive mainly to fast (tens of milliseconds) fluctuations in whisker motion. The topographic organization of whisker sensitivity is paralleled by systematic organization of neuronal selectivity to certain other physical features, but selectivity to touch and to dynamic stimulus properties is distributed in “salt-and-pepper” fashion.